# import torch
# from torch import nn


# src = torch.tensor([[1,2,3,1],[22,12,21,34]], dtype=torch.float)
# print('src.shape:',src.shape)
# print('src:', src)
# final = torch.zeros(src.shape, dtype=torch.float)
# print('final.shape:',final.shape)
# print('final:', final)
# indices = torch.tensor([[1],[0]], dtype=torch.long)
#
#
# result = final.scatter_add(0, indices, src)
# print(result)

# a = torch.tensor([[1,2,3], [9,2,5]])
# b = torch.tensor([[4,1,5], [0,2,6]])
# z = torch.min(a, b)
# print(z)


import numpy as np

x = [(0, 0.20458684329409754), (1, 0.08212673967648215), (2, 0.08665716366408424), (3, 0.1635469987930641)]
print(np.array(x))
# x = np.random.random((4, 10))
# print('x:', x)
# thresh = 20
# ps = np.percentile(x, thresh, axis=1, keepdims=True)
# print('ps:', ps)
# print(np.argwhere(x <= ps))
# print(np.where(x <= ps))
# yy = np.argwhere(x <= ps)
# print(yy[yy[:,0] == 0])
# print(np.where())